Hypoglycemic effects of dracorhodin and dragon blood crude extract from Daemonorops draco.

BACKGROUND: Dragon blood is a red fruit resin from the palm tree Daemonorops draco and is a herbal ingredient used in the traditional Chinese medicine, "Jinchuang Ointment," which is used to treat non-healing diabetic wounds. According to the Taiwan Herbal Pharmacopeia, the dracorhodin content in dragon blood should exceed 1.0%. RESULTS: Our findings indicate that dracorhodin and dragon blood crude extracts can stimulate glucose uptake in mouse muscle cells (C2C12) and primary rat aortic smooth muscle cells (RSMC). Dracorhodin is not the only active compound in dragon blood crude extracts from D. draco. Next, we orally administered crude dragon blood extracts to male B6 mice. The experimental group displayed a decreasing trend in fasting blood glucose levels from the second to tenth week. In summary, crude extracts of dragon blood from D. draco demonstrated in vivo hypoglycemic effects in B6 male mice. CONCLUSIONS: We provide a scientific basis "Jinchuang ointment" in treating non-healing wounds in patients with diabetes.

The future application of artificial intelligence and telemedicine in the retina: A perspective.

The development of artificial intelligence (AI) and deep learning provided precise image recognition and classification in the medical field. Ophthalmology is an exceptional department to translate AI applications since noninvasive imaging is routinely used for the diagnosis and monitoring. In recent years, AI-based image interpretation of optical coherence tomography and fundus photograph in retinal diseases has been extended to diabetic retinopathy, age-related macular degeneration, and retinopathy of prematurity. The rapid development of portable ocular monitoring devices coupled with AI-informed interpretations allows possible home monitoring or remote monitoring of retinal diseases and patients to gain autonomy and responsibility for their conditions. This review discusses the current research and application of AI, telemedicine, and home monitoring devices on retinal disease. Furthermore, we propose a future model of how AI and digital technology could be implemented in retinal diseases.